考虑电磁感应效应的神经元及其网络的动力学研究

The electric activities of neurons are dependent on the complex electrophysiological condition in neuronal system, and it indicates the complex distribution of electromagnetic field could be detected in the neuronal system. According to the Maxwell electromagnetic induction theory, the dynamical behavior in electric activity can be changed due to the effect of internal bioelectricity of nervous system (e.g. fluctuation of ion concentration inside and outside of cell). On the other hand, the electromagnetic flux in the nervous system can be controlled due to electromagnetic radiation when nervous system or media is exposed to external electromagnetic field; furthermore, the collective electric behaviors of neurons could be switched between different modes. This project investigates the problems about modeling the effect of bioelectricity and complex multiscale dynamical properties of nervous system by using the nonlinear science and theory of electro-magnetic induction. It covers, 1) Magnet flux is introduced into the known neuron model and used as additive new variable, so that the response properties for electro-magnetic induction of neuron and network could be described in feasible way. 2) The potential mechanism for magnetic memory of neuron is discussed, and further investigation and verification of the presented model is realized by using FPGA. 3) Transition of multiple modes of neuronal activities in neurons induced by changing bifurcation parameter, the detection of the self-adaptive selection and energy problems when external forcing is imposed on neurons. 4) Synchronization transition of collective behaviors of neurons. These results could give important guidance for cognition, information encoding, and precaution of electromagnetic induction on nervous systems.

神经元电活动与神经系统内复杂的电生理环境密切相关，即神经系统内部存在复杂的电磁场分布。根据麦克斯韦电磁感应理论，神经系统内部的生物电效应(如细胞内外离子浓度涨落)必然对神经元电活动动力学行为产生影响；另一方面，电磁辐射下神经系统或介质的电磁场通量会发生改变，进而引发神经元群体电活动模式的迁移。本项目基于电磁感应理论和非线性科学理论，探究神经系统的生物电效应建模以及复杂多尺度电活动的动力学问题。包括：1) 引入“磁通量”对神经元模型改进，刻画神经元及其神经元网络群体电活动的电磁感应特性；2) 探究神经元磁记忆的机制，改进神经元模型的现场可编程门阵列(FPGA)实现；3)分岔参数诱发的多重放电模式迁移，神经元对外界刺激的自适应性选择机制和能量关联问题；4)神经元群体动力学同步迁移。研究成果可为神经系统的认知，信息编码，电磁辐射预防提供重要信息参考。

神经系统具有复杂的连接结构，不同电磁和生理环境下神经元的模态特征呈现很大差异性。因此，从生物物理角度探究神经元功能连接和自适应性对于认知神经性疾病机理、神经元之间信号和能量输运过程、以及动力学特征等具有重要科学意义。. 主要研究内容：神经元在物理环境下的建模、自突触发育机制和生物功能、哈密顿能量计算和放电模态对哈密顿能量依赖关系、神经元之间场耦合同步、记忆性神经元特征、能量激励下无耦合神经元的同步机理、神经元电路混合突触和场耦合的关联性、功能性神经元建模等。. 重要结果：构建了包含电磁效应的神经元模型、解释了电磁辐射下心脏死亡和休克的两种物理机制，发现神经元在电磁辐射下可以产生多模态并诱发和增强神经元同步。论证了自突触发育的机制和生物功能，即受损的神经元可以通过激活辅助回路来传递电信号，自突触的形成有利于增强神经元的自适应性。在负反馈下，局部神经元被自突触驱动可以在网络中诱发缺陷阻挡信号传递；在正反馈下，局部神经元自突触驱动可以在网络中诱发信号源来调制网络群体行为。解释了微分耦合与积分耦合控制神经元电路和混沌电路的物理依据，为能量注入法控制动力学系统提供了依据。设计了能感知光信号、热信号和外磁场信号的神经元模型和电路、研究了功能性神经元电活动的随机动力学。论证了场耦合对神经元同步稳定性和斑图的作用，为设计可控性的混合突触提供了参考。.发表相关研究论文40余篇被SCI收录，课题组4名硕士毕业生学位论文被评为甘肃省优秀硕士论文，部分研究成果获得2018年甘肃省自然科学奖二等奖。

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